Our understanding of human biology and disease is ultimately dependent on a complete understanding of the genome and its functions. The recent application of microarray and sequencing technologies to transcriptomics has changed the simplistic view of transcriptomes to a more complicated view of genome-wide transcription where a large fraction of transcripts emanates from unannotated parts of genomes, and underlined our limited knowledge of the dynamic state of transcription. Most of this broad body of knowledge was obtained indirectly because current transcriptome analysis methods typically require RNA to be converted to complementary DNA (cDNA) before measurements, even though the cDNA synthesis step introduces multiple biases and artefacts that interfere with both the proper characterization and quantification of transcripts. Furthermore, cDNA synthesis is not particularly suitable for the analysis of short, degraded and/or small quantity RNA samples. Here we report direct single molecule RNA sequencing without prior conversion of RNA to cDNA. We applied this technology to sequence femtomole quantities of poly(A)(+) Saccharomyces cerevisiae RNA using a surface coated with poly(dT) oligonucleotides to capture the RNAs at their natural poly(A) tails and initiate sequencing by synthesis. We observed transcript 3' end heterogeneity and polyadenylated small nucleolar RNAs. This study provides a path to high-throughput and low-cost direct RNA sequencing and achieving the ultimate goal of a comprehensive and bias-free understanding of transcriptomes.
We present single-molecule sequencing digital gene expression (smsDGE), a high-throughput, amplification-free method for accurate quantification of the full range of cellular polyadenylated RNA transcripts using a Helicos Genetic Analysis system. smsDGE involves a reverse-transcription and polyA-tailing sample preparation procedure followed by sequencing that generates a single read per transcript. We applied smsDGE to the transcriptome of Saccharomyces cerevisiae strain DBY746, using 6 of the available 50 channels in a single sequencing run, yielding on average 12 million aligned reads per channel. Using spiked-in RNA, accurate quantitative measurements were obtained over four orders of magnitude. High correlation was demonstrated across independent flow-cell channels, instrument runs and sample preparations. Transcript counting in smsDGE is highly efficient due to the representation of each transcript molecule by a single read. This efficiency, coupled with the high throughput enabled by the single-molecule sequencing platform, provides an alternative method for expression profiling.
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